• Title/Summary/Keyword: paper templates

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Object Tracking with the Multi-Templates Regression Model Based MS Algorithm

  • Zhang, Hua;Wang, Lijia
    • Journal of Information Processing Systems
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    • v.14 no.6
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    • pp.1307-1317
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    • 2018
  • To deal with the problems of occlusion, pose variations and illumination changes in the object tracking system, a regression model weighted multi-templates mean-shift (MS) algorithm is proposed in this paper. Target templates and occlusion templates are extracted to compose a multi-templates set. Then, the MS algorithm is applied to the multi-templates set for obtaining the candidate areas. Moreover, a regression model is trained to estimate the Bhattacharyya coefficients between the templates and candidate areas. Finally, the geometric center of the tracked areas is considered as the object's position. The proposed algorithm is evaluated on several classical videos. The experimental results show that the regression model weighted multi-templates MS algorithm can track an object accurately in terms of occlusion, illumination changes and pose variations.

PAPER TEMPLATES FOR TRIANGULATED SURFACES

  • Min, Cho-Hong
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.15 no.4
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    • pp.307-318
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    • 2011
  • We introduce an algorithm that automatically generates paper templates of a triangulated surface. The surface can be built by cutting, folding, and pasting the paper templates. The algorithm is branched to two strategies : one is to select the longest neghboring edge among many choices, and the other is to select the largest neighboring triangle. Three surfaces, whose triangulation sizes widely range, are successfully built by the algorithm. The two strategies are empirically evaluated in building the surfaces with respect to paper consumption, a measure of cost efficiency, and boundary length, a measure of speed efficiency. Strategy 1 performs in most cases better than the other one with respect to boundary length, but sometimes wins and sometimes loese with respect to paper consumption.

A Study on the Creation Rule of Reference Templates to Recognize Speech for Speaker-independent (불특정 화자의 음성 인식을 위한 표준음 설정 방법에 관한 연구)

  • 김계국;안태옥;이순협;이종악
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.7
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    • pp.715-722
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    • 1988
  • It is very important that we create reference templates to recognize speech of speeker-independent as convergence as possible vocal tract variation of each speaker. We used to clustering technique for this and creation rule of reference templates to be cluster centers is key point of thema. In this paper, we created reference tempaltes using the minimax for existance and MMS technique suggested in this study. Also, we created reference template until top 3 and compared to recognition result. When we create 3 reference templates recognition rate is 91.6% for minimax and recognition rate is 95.8% for MMS.

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A Study on a Human Sensibility Evaluation Technique of EEG using Personality-group Templates (성격 그룹의 템플릿을 이용한 뇌파의 감성평가 기술에 관한 연구)

  • Lee, Sang-Han;Kim, Dong-Jun
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2801-2803
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    • 2003
  • This paper describes a technique for human sensibility evaluation using personality-group templates of EEG(electroencephalogram). 10-channel EEGs of 5 extroverts and 5 introverts are collected in comfortable seat, uncomfortable seat and relaxed state. After preprocessing of EEG, the linear predictor coefficients are extracted and used as feature parameters. A neural network based sensibility classifier is designed and the output of the neural network is assumed as the sensibility index. Multiple templates of two personality-groups are stored and the most similar template can be selected by the proposed method. The proposed method showed the better performance than our previous results which have used ungrouped templates.

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A Knowledge Base Management Technique Based on XML Templates and its Application (XML 템플릿 기반 지식베이스 관리 기법과 그 응용)

  • Lee Hiye-Ja;Jeong Byeong-Soo;Park Seung-Hun
    • The KIPS Transactions:PartD
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    • v.11D no.7 s.96
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    • pp.1527-1536
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    • 2004
  • For using the knowledge of experts diversely and efficiently, it is very important that the system could represent the complex knowledge in well structured manner and also adapt well to the frequent schema changes. In this paper, we propose an efficient method for knowledge base management by using XML based templates. In our proposed method, to solve the inefficiency of management of many XML documents, we represent the complex knowledge on XML-based templates, and manage the templates structurally by using a meta-template that defines relationship among the templates. In order to show the effectiveness of our method, we developed a knowledge base to formulate an exercise prescription for a subject and an application program to classify the subject's fitness. The experimental study shows that XML-based templates provide a flexible, extensible and structured way of representing expert knowledge. The inference using XML-based templates can be controlled systematically and efficiently by using meta-template.

Accurate and Efficient Log Template Discovery Technique

  • Tak, Byungchul
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.10
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    • pp.11-21
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    • 2018
  • In this paper we propose a novel log template discovery algorithm which achieves high quality of discovered log templates through iterative log filtering technique. Log templates are the static string pattern of logs that are used to produce actual logs by inserting variable values during runtime. Identifying individual logs into their template category correctly enables us to conduct automated analysis using state-of-the-art machine learning techniques. Our technique looks at the group of logs column-wise and filters the logs that have the value of the highest proportion. We repeat this process per each column until we are left with highly homogeneous set of logs that most likely belong to the same log template category. Then, we determine which column is the static part and which is the variable part by vertically comparing all the logs in the group. This process repeats until we have discovered all the templates from given logs. Also, during this process we discover the custom patterns such as ID formats that are unique to the application. This information helps us quickly identify such strings in the logs as variable parts thereby further increasing the accuracy of the discovered log templates. Existing solutions suffer from log templates being too general or too specific because of the inability to detect custom patterns. Through extensive evaluations we have learned that our proposed method achieves 2 to 20 times better accuracy.

Development of a Multi-template type Image Segmentation Algorithm for the Recognition of Semiconductor Wafer ID (반도체 웨이퍼 ID 인식을 위한 다중템플릿형 영상분할 알고리즘 개발)

  • Ahn, In-Mo
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.55 no.4
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    • pp.167-175
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    • 2006
  • This paper presents a method to segment semiconductor wafer ID on poor quality images. The method is based on multiple templates and normalized gray-level correlation (NGC) method. If the lighting condition is not so good and hence, we can not control the image quality, target image to be inspected presents poor quality ID and it is not easy to identify and then recognize the ID characters. Conventional several method to segment the interesting ID regions fails on the bad quality images. In this paper, we propose a multiple template method, which uses combinational relation of multiple templates from model templates to match several characters of the inspection images. To find out the optimal solution of multiple template model in ID regions, we introduce newly-developed snake algorithm. Experimental results using images from real FA environment are presented.

Development of an Image Segmentation Algorithm using Dynamic Programming for Object ID Marks in Automation Process (동적계획법을 이용한 자동화 공정에서의 제품 ID 마크 자동분할 알고리듬 개발)

  • 유동훈;안인모;김민성;강동중
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.8
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    • pp.726-733
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    • 2004
  • This paper presents a method to segment object ID(identification) marks on poor quality images under uncontrolled lighting conditions of automated inspection process. The method is based on dynamic programming using multiple templates and normalized gray-level correlation (NGC) method. If the lighting condition is not good and hence, we can not control the image quality, target image to be inspected presents poor quality ID marks and it is not easy to identify and recognize the ID characters. Conventional several methods to segment the interesting ID mark regions fail on the bad quality images. In this paper, we propose a multiple template method, which uses combinational relation of multiple templates from model templates to match several characters of the inspection images. To increase the computation speed to segment the ID mark regions, we introduce the dynamic programming based algorithm. Experimental results using images from real factory automation(FA) environment are presented.

Smooth Path Generation using Hexagonal Cell Representation (육각형 격자를 사용한 부드러운 경로생성)

  • Jung, Dong-Won
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.39 no.12
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    • pp.1124-1132
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    • 2011
  • This paper deals with smooth path generation using B-spline for fixed-wing unmanned aerial vehicles manuevering in 2D environment. Hexagonal cell representation is employed to model the 2D environment, which features increased connectivity among cells over square cell representation. Subsequently, hexagonal cell representation enables smoother path generation based on a discrete sequence of path from the path planner. In addition, we present an on-line path smoothing algorithm incorporating B-spline path templates. The path templates are computed off-line by taking into account all possible path sequences within finite horizon. During on-line implementation, the B-spline curves from the templates are stitched together repeatedly to come up with a reference trajectory for UAVs. This method is an effective way of generating smooth path with reduced on-line computation requirement, hence it can be implemented on a small low-cost autopilot that has limited computational resources.

Multiple Classifier Fusion Method based on k-Nearest Templates (k-최근접 템플릿기반 다중 분류기 결합방법)

  • Min, Jun-Ki;Cho, Sung-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.4
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    • pp.451-455
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    • 2008
  • In this paper, the k-nearest templates method is proposed to combine multiple classifiers effectively. First, the method decomposes training samples of each class into several subclasses based on the outputs of classifiers to represent a class as multiple models, and estimates a localized template by averaging the outputs for each subclass. The distances between a test sample and templates are then calculated. Lastly, the test sample is assigned to the class that is most frequently represented among the k most similar templates. In this paper, C-means clustering algorithm is used as the decomposition method, and k is automatically chosen according to the intra-class compactness and inter-class separation of a given data set. Since the proposed method uses multiple models per class and refers to k models rather than matches with the most similar one, it could obtain stable and high accuracy. In this paper, experiments on UCI and ELENA database showed that the proposed method performed better than conventional fusion methods.